where TP are true positives, FN are false negatives and FP are false positives.
Like the F1 score, the CSI score is not directly applicable to the probability distributions that MetNet-2 produces. To make a categorical decision, for a binary category corresponding to an amount of precipitation greater or equal to a given rate \(r\) , we calculate on held-out data a probability threshold between 0 and 1. If the total predicted probability mass for rates \(\ge r\)  exceeds the threshold, then we take it to be a positive prediction for this rate category. This is the same procedure as used for the F1 score in Sønderby et al. [1]}. We calculate the CSI scores of MetNet-2 on multiple rates ranging from small amounts of precipitation (0.2 mm/hr) to high amounts of precipitation (20 mm/hr).
